class_docstr: An out-of-graph Replay Buffer for Prioritized Experience Replay.
  
  See circular_replay_buffer.py for details.
class_docstr_tok: ["An","out-of-graph","Replay","Buffer","for","Prioritized","Experience","Replay",".","See","circular_replay_buffer.py","for","details","."]
docstr: The signature of the add function.
  
  The signature is the same as the one for OutOfGraphReplayBuffer, with an
  added priority.
  
  Returns:
    list of ReplayElements defining the type of the argument signature needed
      by the add function.
docstr_tok: ["The","signature","of","the","add","function",".","The","signature","is","the","same","as","the","one","for","OutOfGraphReplayBuffer",",","with","an","added","priority",".","Returns",":","list","of","ReplayElements","defining","the","type","of","the","argument","signature","needed","by","the","add","function","."]
code: def get_add_args_signature(self):
      """The signature of the add function.
  
      The signature is the same as the one for OutOfGraphReplayBuffer, with an
      added priority.
  
      Returns:
        list of ReplayElements defining the type of the argument signature needed
          by the add function.
      """
      parent_add_signature = super(
          OutOfGraphPrioritizedReplayBuffer, self
      ).get_add_args_signature()
      add_signature = parent_add_signature + [
          ReplayElement("priority", (), np.float32)
      ]
      return add_signature
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from dopamine.replay_memory import circular_replay_buffer
  from dopamine.replay_memory import sum_tree
  from dopamine.replay_memory.circular_replay_buffer import ReplayElement
  import gin.tf
  import numpy
  import tensorflow
label_desc: Use image node_id 2 for calling the OutOfGraphPrioritizedReplayBuffer obj's underlying member method code with example usage: obj.get_add_args_signature() and returns: add_signature