code: def is_jumpstart_model_uri(uri: Optional[str]) -> bool:
      """Returns True if URI corresponds to a JumpStart-hosted model.
  
      Args:
          uri (Optional[str]): uri for inference/training job.
      """
  
      bucket = None
      if urlparse(uri).scheme == "s3":
          bucket, _ = parse_s3_url(uri)
  
      return (
          bucket in constants.JUMPSTART_GATED_AND_PUBLIC_BUCKET_NAME_SET
      )
  
imports: from __future__ import absolute_import
  import logging
  import os
  from typing import Any, Dict, List, Optional, Union
  from urllib.parse import urlparse
  import boto3
  from packaging.version import Version
  import sagemaker
  from sagemaker.config.config_schema import MODEL_ENABLE_NETWORK_ISOLATION_PATH, MODEL_EXECUTION_ROLE_ARN_PATH, TRAINING_JOB_ENABLE_NETWORK_ISOLATION_PATH, TRAINING_JOB_INTER_CONTAINER_ENCRYPTION_PATH, TRAINING_JOB_ROLE_ARN_PATH
  from sagemaker.jumpstart import constants, enums
  from sagemaker.jumpstart import accessors
  from sagemaker.s3 import parse_s3_url
  from sagemaker.jumpstart.exceptions import DeprecatedJumpStartModelError, VulnerableJumpStartModelError, get_old_model_version_msg
  from sagemaker.jumpstart.types import JumpStartModelHeader, JumpStartModelSpecs, JumpStartVersionedModelId
  from sagemaker.session import Session
  from sagemaker.config import load_sagemaker_config
  from sagemaker.utils import resolve_value_from_config, TagsDict
  from sagemaker.workflow import is_pipeline_variable
label_desc: Use image node_id 8 for calling a global function with example usage: is_jumpstart_model_uri(uri) and returns: unknown