code: def update_inference_tags_with_jumpstart_training_tags(
      inference_tags: Optional[List[Dict[str, str]]],
      training_tags: Optional[List[Dict[str, str]]],
  ) -> Optional[List[Dict[str, str]]]:
      """Updates the tags for the ``sagemaker.model.Model.deploy`` command with any JumpStart tags.
  
      Args:
          inference_tags (Optional[List[Dict[str, str]]]): Custom tags to appy to inference job.
          training_tags (Optional[List[Dict[str, str]]]): Tags from training job.
      """
      if training_tags:
          for tag_key in enums.JumpStartTag:
              if tag_key_in_array(tag_key, training_tags):
                  tag_value = get_tag_value(tag_key, training_tags)
                  if inference_tags is None:
                      inference_tags = []
                  if not tag_key_in_array(tag_key, inference_tags):
                      inference_tags.append(
                          {"Key": tag_key, "Value": tag_value}
                      )
  
      return inference_tags
  
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 15 for calling a global function with example usage: update_inference_tags_with_jumpstart_training_tags(inference_tags, training_tags) and returns: inference_tags