code: def load_memory(self):
      container = np.load(self.file_path, allow_pickle=True)
      [
          self.obs,
          self.reward,
          self.action,
          self.isOver,
          self._curr_size,
          self._curr_pos,
          self._context,
      ] = [container[key] for key in container]
      self._curr_size = self._curr_size.astype(int)
      self._curr_pos = self._curr_pos.astype(int)
      self._context = deque(
          [Experience(*row) for row in self._context],
          maxlen=self.context_len - 1,
      )
  
file_path: PARL/benchmark/fluid/offline-Q-learning/replay_memory.py
imports: import numpy
  import copy
  import os
  from collections import deque, namedtuple
  from parl.utils import logger
label_desc: Use image node_id 12 for calling the ReplayMemory obj's underlying member method code with example usage: obj.load_memory() without return types