class_docstr: A Kubernetes job runner that launches and executes pipeline components in kubernetes cluster.
docstr: Create a kubernetes model server runner.
  
  Args:
    tfx_image: container image for tfx.
    job_prefix: prefix for the job. Unique hash will follow as suffix.
    container_name: name of the container.
    name_space: namespace of the run.
    stream_logs: whether to stream logs from the pod.
docstr_tok: ["Create","a","kubernetes","model","server","runner",".","Args",":","tfx_image",":","container","image","for","tfx",".","job_prefix",":","prefix","for","the","job",".","Unique","hash","will","follow","as","suffix",".","container_name",":","name","of","the","container",".","name_space",":","namespace","of","the","run",".","stream_logs",":","whether","to","stream","logs","from","the","pod","."]
code: def __init__(
      self,
      tfx_image,
      job_prefix,
      container_name,
      name_space="default",
      stream_logs=False,
  ):
      """Create a kubernetes model server runner.
  
      Args:
        tfx_image: container image for tfx.
        job_prefix: prefix for the job. Unique hash will follow as suffix.
        container_name: name of the container.
        name_space: namespace of the run.
        stream_logs: whether to stream logs from the pod.
      """
      self._image = tfx_image
      self._k8s_core_api = kube_utils.make_core_v1_api()
      self._namespace = name_space
      self._container_name = container_name
      self._job_name = kube_utils.sanitize_pod_name(
          job_prefix + _generate_component_name_suffix()
      )
      # Time to delete the job after completion.
      self.ttl_seconds = 5
      # Pod name would be populated once creation request sent.
      self._pod_name = None
      self._stream_pod_logs = stream_logs
  
imports: import abc
  import datetime
  import random
  import string
  import time
  from absl import logging
  from kubernetes import client
  from tfx.orchestration.experimental.core import task_scheduler
  from tfx.orchestration.python_execution_binary import python_execution_binary_utils
  from tfx.utils import kube_utils
  from tfx.utils import status
label_desc: Use image node_id 1 to create a new KubernetesJobRunner object from inherited base classes: abc with example: obj = KubernetesJobRunner(tfx_image, job_prefix, container_name, name_space, stream_logs)