class_docstr: Set hyperparameter by loading the value from a file each time it get called.
  This is useful for manually tuning some parameters (e.g. learning_rate)
  without interrupting the training.
code: def _get_value_to_set(self):
      # ignore if no such file exists
      if not os.path.isfile(self.file_name):
          return None
      try:
          with open(self.file_name) as f:
              lines = f.readlines()
          lines = [s.strip().split(":") for s in lines]
          dic = {str(k): float(v) for k, v in lines}
          ret = dic[self.param.readable_name]
          return ret
      except Exception:
          logger.warn(
              "Cannot find {} in {}".format(
                  self.param.readable_name, self.file_name
              )
          )
          return None
  
imports: import operator
  import os
  import numpy
  from abc import ABCMeta, abstractmethod
  from collections import deque
  import six
  from ..compat import tfv1
  from ..tfutils.common import get_op_tensor_name
  from ..utils import logger
  from .base import Callback
label_desc: Use image node_id 2 for calling the HumanHyperParamSetter obj's underlying member method code with example usage: obj._get_value_to_set() and returns: None, ret, None