code: def try_to_load_from_cache(
      repo_id: str,
      filename: str,
      cache_dir: Union[str, Path, None] = None,
      revision: Optional[str] = None,
  ) -> Optional[str]:
      """
      Explores the cache to return the latest cached file for a given revision if found.
  
      This function will not raise any exception if the file in not cached.
  
      Args:
          cache_dir (`str` or `os.PathLike`):
              The folder where the cached files lie.
          repo_id (`str`):
              The ID of the repo on huggingface.co.
          filename (`str`):
              The filename to look for inside `repo_id`.
          revision (`str`, *optional*):
              The specific model version to use. Will default to `"main"` if it's not provided and no `commit_hash` is
              provided either.
  
      Returns:
          `Optional[str]` or `_CACHED_NO_EXIST`:
              Will return `None` if the file was not cached. Otherwise:
              - The exact path to the cached file if it's found in the cache
              - A special value `_CACHED_NO_EXIST` if the file does not exist at the given commit hash and this fact was
                cached.
      """
      if revision is None:
          revision = "main"
  
      if cache_dir is None:
          cache_dir = TRANSFORMERS_CACHE
  
      object_id = repo_id.replace("/", "--")
      repo_cache = os.path.join(cache_dir, f"models--{object_id}")
      if not os.path.isdir(repo_cache):
          # No cache for this model
          return None
      for subfolder in ["refs", "snapshots"]:
          if not os.path.isdir(os.path.join(repo_cache, subfolder)):
              return None
  
      # Resolve refs (for instance to convert main to the associated commit sha)
      cached_refs = os.listdir(os.path.join(repo_cache, "refs"))
      if revision in cached_refs:
          with open(os.path.join(repo_cache, "refs", revision)) as f:
              revision = f.read()
  
      if os.path.isfile(
          os.path.join(repo_cache, ".no_exist", revision, filename)
      ):
          return _CACHED_NO_EXIST
  
      cached_shas = os.listdir(os.path.join(repo_cache, "snapshots"))
      if revision not in cached_shas:
          # No cache for this revision and we won't try to return a random revision
          return None
  
      cached_file = os.path.join(
          repo_cache, "snapshots", revision, filename
      )
      return cached_file if os.path.isfile(cached_file) else None
  
imports: import json
  import os
  import re
  import shutil
  import sys
  import tempfile
  import traceback
  import warnings
  from pathlib import Path
  from typing import Dict, List, Optional, Tuple, Union
  from urllib.parse import urlparse
  from uuid import uuid4
  import huggingface_hub
  import requests
  from huggingface_hub import CommitOperationAdd, HfFolder, create_commit, create_repo, get_hf_file_metadata, hf_hub_download, hf_hub_url, whoami
  from huggingface_hub.file_download import REGEX_COMMIT_HASH, http_get
  from huggingface_hub.utils import EntryNotFoundError, LocalEntryNotFoundError, RepositoryNotFoundError, RevisionNotFoundError, hf_raise_for_status
  from requests.exceptions import HTTPError
  from transformers.utils.logging import tqdm
  from .None import __version__, logging
  from .generic import working_or_temp_dir
  from .import_utils import ENV_VARS_TRUE_VALUES, _tf_version, _torch_version, is_tf_available, is_torch_available, is_training_run_on_sagemaker
label_desc: Use image node_id 7 for calling a global function with example usage: try_to_load_from_cache(repo_id, filename, cache_dir, revision) and returns: unknown, None, _CACHED_NO_EXIST, None, None