code: def deque_sample(self, indices):
      for i in indices:
          s = self.replay_memory[i]
          yield s.state, s.action, s.next_state, s.reward, s.not_terminal
  
imports: import logging
  from collections import deque
  from typing import NamedTuple
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from reagent.core import types
  from reagent.core.torch_utils import stack
  from torch.distributions.normal import Normal
label_desc: Use image node_id 2 for calling the MDNRNNMemoryPool obj's underlying member method code with example usage: obj.deque_sample(indices) without return types