class_docstr: Manage the double for loop.
docstr: The number of steps that have finished in the current epoch.
docstr_tok: ["The","number","of","steps","that","have","finished","in","the","current","epoch","."]
code: def local_step(self):
      """
      The number of steps that have finished in the current epoch.
      """
      return self._local_step
  
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 6 for calling the TrainLoop obj's underlying member method code with example usage: obj.local_step() and returns: self