class_docstr: A simple out-of-graph Replay Buffer.
  
  Stores transitions, state, action, reward, next_state, terminal (and any
  extra contents specified) in a circular buffer and provides a uniform
  transition sampling function.
  
  When the states consist of stacks of observations storing the states is
  inefficient. This class writes observations and constructs the stacked states
  at sample time.
  
  Attributes:
    add_count: int, counter of how many transitions have been added (including
      the blank ones at the beginning of an episode).
    invalid_range: np.array, an array with the indices of cursor-related invalid
      transitions
    episode_end_indices: set[int], a set of indices corresponding to the
      end of an episode.
docstr: Return the dict of elements of the class for checkpointing.
  
  Returns:
    checkpointable_elements: dict containing all non private (starting with
    _) members + all the arrays inside self._store.
docstr_tok: ["Return","the","dict","of","elements","of","the","class","for","checkpointing",".","Returns",":","checkpointable_elements",":","dict","containing","all","non","private","(","starting","with","_",")","members","+","all","the","arrays","inside","self._store","."]
code: def _return_checkpointable_elements(self):
      """Return the dict of elements of the class for checkpointing.
  
      Returns:
        checkpointable_elements: dict containing all non private (starting with
        _) members + all the arrays inside self._store.
      """
      checkpointable_elements = {}
      for member_name, member in self.__dict__.items():
          if member_name == "_store":
              for array_name, array in self._store.items():
                  checkpointable_elements[
                      STORE_FILENAME_PREFIX + array_name
                  ] = array
          elif not member_name.startswith("_"):
              checkpointable_elements[member_name] = member
      return checkpointable_elements
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import gzip
  import math
  import os
  import pickle
  from absl import logging
  import gin.tf
  import numpy
  import tensorflow
label_desc: Use image node_id 25 for calling the OutOfGraphReplayBuffer obj's underlying member method code with example usage: obj._return_checkpointable_elements() and returns: checkpointable_elements