code: def _process_batch(self, batch_exp):
      obs = np.asarray([e[0] for e in batch_exp], dtype="uint8")
      reward = np.asarray([e[1] for e in batch_exp], dtype="float32")
      action = np.asarray([e[2] for e in batch_exp], dtype="int8")
      isOver = np.asarray([e[3] for e in batch_exp], dtype="bool")
      return [obs, action, reward, isOver]
  
file_path: PARL/benchmark/fluid/DQN_variant/replay_memory.py
imports: import numpy
  import copy
  from collections import deque, namedtuple
label_desc: Use image node_id 9 for calling the ReplayMemory obj's underlying member method code with example usage: obj._process_batch(batch_exp) and returns: list