code: def run_kubernetes_job(
      project_name,
      active_run,
      image_tag,
      image_digest,
      command,
      env_vars,
      kube_context=None,
      job_template=None,
  ):
      job_template = _get_kubernetes_job_definition(
          project_name,
          image_tag,
          image_digest,
          _get_run_command(command),
          env_vars,
          job_template,
      )
      job_name = job_template["metadata"]["name"]
      job_namespace = job_template["metadata"]["namespace"]
      _load_kube_context(context=kube_context)
      api_instance = kubernetes.client.BatchV1Api()
      api_instance.create_namespaced_job(
          namespace=job_namespace, body=job_template, pretty=True
      )
      return KubernetesSubmittedRun(
          active_run.info.run_id, job_name, job_namespace
      )
  
imports: import logging
  import os
  import time
  from datetime import datetime
  from shlex import quote, split
  from threading import RLock
  import kubernetes
  from kubernetes.config.config_exception import ConfigException
  import docker
  from mlflow.entities import RunStatus
  from mlflow.exceptions import ExecutionException
  from mlflow.projects.submitted_run import SubmittedRun
label_desc: Use image node_id 5 for calling a global function with example usage: run_kubernetes_job(project_name, active_run, image_tag, image_digest, command, env_vars, kube_context, job_template) and returns: KubernetesSubmittedRun