class_docstr: An orchestrator implmentation which uses Kubernetes to deploy the components such as training and rollout workers
  and Redis Pub/Sub in Coach when used in the distributed mode.
class_docstr_tok: ["An","orchestrator","implmentation","which","uses","Kubernetes","to","deploy","the","components","such","as","training","and","rollout","workers","and","Redis","Pub\/Sub","in","Coach","when","used","in","the","distributed","mode","."]
code: def _tail_log_file(self, pod_name, api_client, namespace, path):
      if not os.path.exists(path):
          os.mkdir(path)
  
      sys.stdout = open(os.path.join(path, pod_name), "w")
      self.tail_log(pod_name, api_client)
  
imports: import os
  import uuid
  import json
  import time
  import sys
  from enum import Enum
  from typing import List
  from configparser import ConfigParser, Error
  from multiprocessing import Process
  from rl_coach.base_parameters import RunType
  from rl_coach.orchestrators.deploy import Deploy, DeployParameters
  from kubernetes import client, config
  from rl_coach.memories.backend.memory import MemoryBackendParameters
  from rl_coach.memories.backend.memory_impl import get_memory_backend
  from rl_coach.data_stores.data_store import DataStoreParameters
  from rl_coach.data_stores.data_store_impl import get_data_store
  from rl_coach.logger import screen
label_desc: Use image node_id 6 for calling the Kubernetes obj's underlying member method code with example usage: obj._tail_log_file(pod_name, api_client, namespace, path) without return types