class_docstr: Replay memory to store samples of experience.
  
  Each transition is represented as (state, action, reward, next_state,
  priority) tuple. 'priority' is ignored for non-prioritized experience
  replay.
class_docstr_tok: ["Replay","memory","to","store","samples","of","experience",".","Each","transition","is","represented","as","(","state",",","action",",","reward",",","next_state",",","priority",")","tuple",".","'priority","'","is","ignored","for","non-prioritized","experience","replay","."]
docstr: Return the current number of transitions.
docstr_tok: ["Return","the","current","number","of","transitions","."]
code: def size(self):
      """Return the current number of transitions."""
      l = len(self._memory)
      if self._use_prioritized_replay:
          l -= self._capacity - 1
      return l
  
file_path: CNTK/bindings/python/cntk/contrib/deeprl/agent/shared/replay_memory.py
imports: from __future__ import division
  import math
  import random
  from collections import namedtuple
label_desc: Use image node_id 8 for calling the ReplayMemory obj's underlying member method code with example usage: obj.size() and returns: l