def __init__(self,
               save_steps=100,
               output_dir=None,
               summary_writer=None,
               scaffold=None,
               summary_op=None):
    """Initializes a `SummarySaver` monitor.

    Args:
      save_steps: `int`, save summaries every N steps. See `EveryN`.
      output_dir: `string`, the directory to save the summaries to. Only used
          if no `summary_writer` is supplied.
      summary_writer: `SummaryWriter`. If `None` and an `output_dir` was passed,
          one will be created accordingly.
      scaffold: `Scaffold` to get summary_op if it's not provided.
      summary_op: `Tensor` of type `string`. A serialized `Summary` protocol
          buffer, as output by TF summary methods like `scalar_summary` or
          `merge_all_summaries`.
    """
    # TODO(ipolosukhin): Implement every N seconds.
    self._summary_op = summary_op
    self._summary_writer = summary_writer
    if summary_writer is None and output_dir:
      self._summary_writer = SummaryWriterCache.get(output_dir)
    self._scaffold = scaffold
    self._save_steps = save_steps

 def __init__(self, every_n_steps=100, output_dir=None, summary_writer=None):
     super(StepCounter, self).__init__(every_n_steps=every_n_steps)
     self._summary_tag = "global_step/sec"
     self._last_reported_step = None
     self._last_reported_time = None
     self._summary_writer = summary_writer
     if summary_writer is None and output_dir:
         self._summary_writer = SummaryWriterCache.get(output_dir)

  def __init__(self, every_n_steps, saver, checkpoint_dir,
               checkpoint_basename="model.ckpt",
               first_n_steps=-1):
    """Initialize CheckpointSaver monitor.

    Args:
      every_n_steps: `int`, save every N steps.
      saver: `Saver` object, used for saving.
      checkpoint_dir: `str`, base directory for the checkpoint files.
      checkpoint_basename: `str`, base name for the checkpoint files.
      first_n_steps: `int`, if positive, save every step during the
        first `first_n_steps` steps.
    """
    logging.info("Create CheckpointSaver")
    super(CheckpointSaver, self).__init__(every_n_steps=every_n_steps,
                                          first_n_steps=first_n_steps)
    self._saver = saver
    self._summary_writer = SummaryWriterCache.get(checkpoint_dir)
    self._save_path = os.path.join(checkpoint_dir, checkpoint_basename)

 def set_estimator(self, estimator):
   super(StepCounter, self).set_estimator(estimator)
   if self._summary_writer is None:
     self._summary_writer = SummaryWriterCache.get(estimator.model_dir)