class_docstr: Class-wrapper for a process that persist for a long time. The process
  may be initialized with any handler requirements. Current implimentation
  is based on ProcessPoolExecutor just because of multiprocessing.pool
  produce daemon processes, which can not be used for learning. That
  bahaviour may be changed only using inheritance.
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docstr: remember that that process processed task for that model
  
  Args:
      marker (tuple): identifier of model
docstr_tok: ["remember","that","that","process","processed","task","for","that","model","Args",":","marker","(","tuple",")",":","identifier","of","model"]
code: def add_marker(self, marker: tuple):
      """remember that that process processed task for that model
  
      Args:
          marker (tuple): identifier of model
      """
      if marker is not None:
          self._markers.add(marker)
  
imports: import sys
  import time
  import threading
  from typing import Optional, Callable
  from concurrent.futures import ProcessPoolExecutor, Future
  from pandas import DataFrame
  from mindsdb.utilities.config import Config
  from mindsdb.utilities.context import context
  from mindsdb.utilities.ml_task_queue.const import ML_TASK_TYPE
  from mindsdb.integrations.libs.learn_process import learn_process, predict_process
label_desc: Use image node_id 8 for calling the WarmProcess obj's underlying member method code with example usage: obj.add_marker(marker) without return types