class_docstr: Replay Buffer for storing past experiences allowing the agent to learn from them.
  
  >>> ReplayBuffer(5)  # doctest: +ELLIPSIS
  <...reinforce_learn_Qnet.ReplayBuffer object at ...>
docstr: Add experience to the buffer.
  
  Args:
      experience: tuple (state, action, reward, done, new_state)
docstr_tok: ["Add","experience","to","the","buffer",".","Args",":","experience",":","tuple","(","state",",","action",",","reward",",","done",",","new_state",")"]
code: def append(self, experience: Experience) -> None:
      """Add experience to the buffer.
  
      Args:
          experience: tuple (state, action, reward, done, new_state)
  
      """
      self.buffer.append(experience)
  
imports: import argparse
  from collections import OrderedDict, deque, namedtuple
  from typing import Iterator, List, Tuple
  import gym
  import numpy
  import torch
  import torch.nn
  import torch.optim
  from lightning.pytorch import LightningModule, Trainer, cli_lightning_logo, seed_everything
  from torch.optim.optimizer import Optimizer
  from torch.utils.data import DataLoader
  from torch.utils.data.dataset import IterableDataset
label_desc: Use image node_id 3 for calling the ReplayBuffer obj's underlying member method code with example usage: obj.append(experience) without return types