class_docstr: Instance of SubmittedRun corresponding to a Kubernetes Job run launched to run an MLflow
  project.
  :param mlflow_run_id: ID of the MLflow project run.
  :param job_name: Kubernetes job name.
  :param job_namespace: Kubernetes job namespace.
class_docstr_tok: ["Instance","of","SubmittedRun","corresponding","to","a","Kubernetes","Job","run","launched","to","run","an","MLflow","project",".",":","param","mlflow_run_id",":","ID","of","the","MLflow","project","run",".",":","param","job_name",":","Kubernetes","job","name",".",":","param","job_namespace",":","Kubernetes","job","namespace","."]
code: def __init__(self, mlflow_run_id, job_name, job_namespace):
      super().__init__()
      self._mlflow_run_id = mlflow_run_id
      self._job_name = job_name
      self._job_namespace = job_namespace
      self._status = RunStatus.SCHEDULED
      self._status_lock = RLock()
      self._kube_api = kubernetes.client.BatchV1Api()
  
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 1 to create a new KubernetesSubmittedRun object from inherited base classes: SubmittedRun with example: obj = KubernetesSubmittedRun(mlflow_run_id, job_name, job_namespace)