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: Args:
      capacity: size of the buffer
docstr_tok: ["Args",":","capacity",":","size","of","the","buffer"]
code: def __init__(self, capacity: int) -> None:
      """
      Args:
          capacity: size of the buffer
      """
      self.buffer = deque(maxlen=capacity)
  
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 1 to create a new ReplayBuffer object  with example: obj = ReplayBuffer(capacity)