class_docstr: Manage the double for loop.
code: def __init__(self):
      self._epoch_num = 0
      self._global_step = 0
      self._local_step = -1
  
imports: import copy
  import time
  import weakref
  import tensorflow
  from ..compat import tfv1
  from ..callbacks import Callback, Callbacks, Monitors, MonitorBase
  from ..callbacks.steps import MaintainStepCounter
  from ..tfutils import get_global_step_value
  from ..tfutils.model_utils import describe_trainable_vars
  from ..tfutils.sesscreate import NewSessionCreator, ReuseSessionCreator
  from ..tfutils.sessinit import JustCurrentSession, SessionInit
  from ..utils import logger
  from ..utils.argtools import call_only_once
  from ..utils.utils import humanize_time_delta
  from .config import DEFAULT_CALLBACKS, DEFAULT_MONITORS, TrainConfig
label_desc: Use image node_id 1 to create a new TrainLoop object from inherited base classes: object with example: obj = TrainLoop()