code: def get_huggingface_llm_image_uri(
      backend: str,
      session: Optional[Session] = None,
      region: Optional[str] = None,
      version: Optional[str] = None,
  ) -> str:
      """Retrieves the image URI for inference.
  
      Args:
          backend (str): The backend to use. Valid values include "huggingface" and "lmi".
          session (Session): The SageMaker Session to use. (Default: None).
          region (str): The AWS region to use for image URI. (default: None).
          version (str): The framework version for which to retrieve an
              image URI. If no version is set, defaults to latest version. (default: None).
  
      Returns:
          str: The image URI string.
      """
  
      if region is None:
          if session is None:
              region = Session().boto_session.region_name
          else:
              region = session.boto_session.region_name
      if backend == "huggingface":
          return image_uris.retrieve(
              "huggingface-llm",
              region=region,
              version=version,
              image_scope="inference",
          )
      if backend == "lmi":
          version = version or "0.24.0"
          return image_uris.retrieve(
              framework="djl-deepspeed", region=region, version=version
          )
      raise ValueError("Unsupported backend: %s" % backend)
  
file_path: sagemaker-python-sdk/src/sagemaker/huggingface/llm_utils.py
imports: from __future__ import absolute_import
  from typing import Optional
  import urllib.request
  from urllib.error import HTTPError, URLError
  import json
  from json import JSONDecodeError
  import logging
  from sagemaker import image_uris
  from sagemaker.session import Session
label_desc: Use image node_id 1 for calling a global function with example usage: get_huggingface_llm_image_uri(backend, session, region, version) and returns: image_uris, image_uris