code: def resolve_adapter_path(
      adapter_name_or_path,
      model_name: str = None,
      adapter_config: Union[dict, str] = None,
      version: str = None,
      source: str = None,
      **kwargs,
  ) -> str:
      """
      Resolves the path to a pre-trained adapter module. Note: If attempting to resolve an adapter from the Hub,
      adapter_config and model_name must be present.
  
      Args:
          adapter_name_or_path (str): Can be either:
  
              - the path to a folder in the file system containing the adapter configuration and weights
              - an url pointing to a zip folder containing the adapter configuration and weights
              - a specifier matching a pre-trained adapter uploaded to Adapter-Hub
          model_name (str, optional): The identifier of the pre-trained model for which to load an adapter.
          adapter_config (Union[dict, str], optional): The configuration of the adapter to be loaded.
          version (str, optional): The version of the adapter to be loaded. Defaults to None.
          source (str, optional): Identifier of the source(s) from where to get adapters. Can be either:
  
              - "ah": search on AdapterHub.ml.
              - "hf": search on HuggingFace model hub (huggingface.co).
              - None (default): search on all sources
  
      Returns:
          str: The local path from where the adapter module can be loaded.
      """
      # url of a folder containing pretrained adapters -> try to load from this url
      if is_remote_url(adapter_name_or_path):
          resolved_folder = download_cached(
              adapter_name_or_path, **kwargs
          )
          if not resolved_folder:
              raise EnvironmentError(
                  "Unable to load file from {}. The file might be unavailable.".format(
                      resolved_folder
                  )
              )
          return resolved_folder
      # path to a local folder saved using save()
      elif isdir(adapter_name_or_path):
          if isfile(
              join(adapter_name_or_path, WEIGHTS_NAME)
          ) and isfile(join(adapter_name_or_path, CONFIG_NAME)):
              return adapter_name_or_path
          else:
              raise EnvironmentError(
                  "No file {} or no file {} found in directory {}".format(
                      WEIGHTS_NAME, CONFIG_NAME, adapter_name_or_path
                  )
              )
      elif source == "ah":
          return pull_from_hub(
              adapter_name_or_path,
              model_name,
              adapter_config=adapter_config,
              version=version,
              **kwargs,
          )
      elif source == "hf":
          return pull_from_hf_model_hub(
              adapter_name_or_path, version=version, **kwargs
          )
      elif source is None:
          try:
              logger.info(
                  "Attempting to load adapter from source 'ah'..."
              )
              return pull_from_hub(
                  adapter_name_or_path,
                  model_name,
                  adapter_config=adapter_config,
                  version=version,
                  **kwargs,
              )
          except EnvironmentError as ex:
              logger.info(ex)
              logger.info(
                  "Attempting to load adapter from source 'hf'..."
              )
              try:
                  return pull_from_hf_model_hub(
                      adapter_name_or_path, version=version, **kwargs
                  )
              except Exception as ex:
                  logger.info(ex)
                  raise EnvironmentError(
                      "Unable to load adapter {} from any source. Please check the name of the adapter or the source.".format(
                          adapter_name_or_path
                      )
                  )
      else:
          raise ValueError(
              "Unable to identify {} as a valid module location.".format(
                  adapter_name_or_path
              )
          )
  
imports: import ast
  import fnmatch
  import hashlib
  import inspect
  import io
  import json
  import logging
  import os
  import re
  import shutil
  import tarfile
  import tempfile
  from collections.abc import Mapping
  from contextlib import contextmanager
  from dataclasses import dataclass
  from enum import Enum
  from functools import partial
  from os.path import basename, isdir, isfile, join
  from pathlib import Path
  from typing import Callable, Dict, List, Optional, Tuple, Union
  from urllib.parse import urlparse
  from zipfile import ZipFile, is_zipfile
  import torch
  import requests
  from filelock import FileLock
  from huggingface_hub import HfApi, HfFolder, snapshot_download
  from huggingface_hub.file_download import http_get, url_to_filename
  from huggingface_hub.utils import EntryNotFoundError, RepositoryNotFoundError, RevisionNotFoundError, hf_raise_for_status
  from requests.exceptions import HTTPError
  from transformers.utils import http_user_agent, is_remote_url
  from transformers.utils.hub import torch_cache_home
  from .None import __version__
  from .context import ForwardContext
label_desc: Use image node_id 18 for calling a global function with example usage: resolve_adapter_path(adapter_name_or_path, model_name, adapter_config, version, source) and returns: resolved_folder, adapter_name_or_path, pull_from_hub, pull_from_hf_model_hub, pull_from_hub, pull_from_hf_model_hub